funsor
pyro
| funsor | pyro | |
|---|---|---|
| 1 | 9 | |
| 233 | 8,384 | |
| 1.7% | 0.8% | |
| 3.3 | 8.4 | |
| 9 months ago | 7 days ago | |
| Python | Python | |
| Apache License 2.0 | Apache License 2.0 |
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funsor
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Functions are Vectors
Plug for the Funsor library, written by Eli Bingham and me for use in the Pyro and NumPyro probabilistic programming languages. We tried to take the "functions are tensors" perspective and make a numpy-like library for functions, aimed mostly at the log-density functions of probability distributions.
Paper: "Functional Tensors for Probabilistic Programming" (2019) https://arxiv.org/abs/1910.10775
Code: https://github.com/pyro-ppl/funsor
pyro
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Show HN: Designing Bridges with PyTorch
Mostly I use pytorch for statistical modeling https://pyro.ai . Under the hood that package uses a lot of Monte Carlo integration and variational methods (i.e. integration by optimization). It does support neural nets, but probably >80% of pyro users stick to simpler hierarchical Bayesian models.
- Pyro: The Universal, Probablistic Programming Language
- The Jupyter+Git problem is now solved
- Pyro: Deep universal probabilistic programming with Python and PyTorch
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Computational Bayesian Inference Techniques
Amortized Variational Inference (Like done in pyro.ai with neural networks)
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[P] torchegranate: a PyTorch rewrite of the pomegranate library for probabilistic modeling
Can you compare this to Pyro, which is also built on top of PyTorch?
- [Q] Updated book or review paper on MCMC methods
- Is anyone here working in uncertainty estimation in neural networks?
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[D] Do you train and deploy models using just one framework or multiple frameworks at work?
Using pyod, statmodels, scikit-learn, Tensorflow and pyro.ai (that is using PyTorch as backend). I always use the same framework for training and for production.
What are some alternatives?
pyprobml - Python code for "Probabilistic Machine learning" book by Kevin Murphy
PyMC - Bayesian Modeling and Probabilistic Programming in Python
lightwood - Lightwood is Legos for Machine Learning.
scikit-learn - scikit-learn: machine learning in Python
numpyro - Probabilistic programming with NumPy powered by JAX for autograd and JIT compilation to GPU/TPU/CPU.
Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
ivy - The Unified AI Framework
trueskill - An implementation of the TrueSkill rating system for Python
probability - Probabilistic reasoning and statistical analysis in TensorFlow
Keras - Deep Learning for humans
tensorflow - An Open Source Machine Learning Framework for Everyone
MLflow - Open source platform for the machine learning lifecycle